The invention described in this patent application relates to the field of code-division-multiple-access (CDMA) wireless systems with multipath fading, and in particular to a method for estimating signature waveforms associated with the subscribers by means of subspace decomposition and least-squares fitting.
The rapid increase in the number of users of mobile telephones, personal communication services (PCS), etc., places challenging demands on future wireless services. Viewed as the generic next generation commercial multiplexing scheme, CDMA offers the promises of efficient use of the available bandwidth, inherent resistance to interference and adaptability to variable traffic patterns. If all mobile radio signals arriving at the base station are synchronized to within a small fraction of a chip-time interval, then it is possible to reduce the level mutual interference dramatically. For such synchronous CDMA (S-CDMA) systems, the use of orthogonal codewords can enhance performance to a greater degree than in asynchronous-CDMA systems (M K. Simon et al, "Spread Spectrum Communications Handbook", McGraw-Hill, New York, N.Y., revised edition, 1994).
In some applications where multipath delays are not negelible, it is normally difficult to maintain the low cross correlation among subscribers' signature waveforms since communication channels are subject to frequency-selective fading. Signal reception using conventional matched filters may suffer severe performance degradation due to mutual interference, especially in a near-far situation (e.g., weak CDMA signals can be overwhelmed by strong power signals in the same system). To mitigate this problem, multiuser detection/equalization needs to be performed to cope with frequency-selective fading. A class of multiuser receivers have been developed. The most prominent ones among many other include R. Lupas and S. Verdu, "Linear multiuser detectors for synchronous CDMA channels"IEEE Trans. on Information Theory, 1(35):123-136, January 1989.; Z. Xie et al, "A family of sub-optimum detectors for coherent multiuser communications", IEEE J. Selected Areas in Communications, pages 683-690, May 1990; and Z. Zvonar and D. Brady, "Suboptimum multiuser detector for synchronous CDMA frequency-selective Rayleigh fading channels", Globecom Mini-Conference on Communications Theory, pages 82-86, 1992.
Almost all the multiuser detectors require explicit knowledge of all users' signature waveforms which is the convolution of the multipath channels and the users' spreading codes. The signature waveforms distinct one CDMA signal from another. Conventional approaches for estimating the signature waveforms in a possibly time-varying environment, e.g., mobile applications, rely on a periodic transmission of a pilot signal (training sequence); the procedure is standard and can be found in a number of texts (e.g., see S. Haykin, "Adaptive Filter Theory", Prentice-Hall, Englewood Cliffs, N.J., second edition, 1991). The price paid is a significant reduction in channel efficiency and system robustness. As the rate of channel variations increases, the use of training sequences may become prohibitive. Also, the training sequences in the CDMA environments are not so effective as in the TDMA (Time-Division-Multiple-Access) scenarios due to high interference level in the CDMA environments. Adaptive multiuser detection has been proposed to combat fast fading channels. Recently developed algorithms include U. Mitra and H. V. Poor, "Adaptive receiver algorithm for near-far resistant CDMA", IEEE Trans. on Communications, 43(4):1713-1724, April 1995; M. Abdulrahman et al, "Equalization for interference cancellation in spread spectrum multiple access systems", Proc. VTC'92, pages 71-74, May 1992; P. Rapajic and B. Vucetic, "A linear adaptive fractionally spaced single user receiver for asynchronous CDMA systems", IEEE Int. Symp. on Information Theory, page 45, January 1993; and Honig et al, "Blind adaptive interference suppression for near-far resistant CDMA", Proc. Globecom'94, pages 379-384, 1994. Despite its success in some scenarios, the adaptive reception scheme still requires pilot signals to obtain a precise estimate of the signature waveform, at least that of a desired user.
Currently state-of-the-art technology can determine the channel without the use of a training sequence (herein referred to as blind identification). One of the earliest approach which utilizes low-order statistics was introduced by Tong et al., (Tong et al., "Blind Identification and Equalization Based on Second-Order Statistics: A Time Domain Approach", IEEE Trans. on Information Theory, March, 1994). Latest results show that the requirement for input statistics can be eliminated--blind identification can be accomplished based solely on a limited number of outputs (H. Liu et al, "Recent Developments in Blind Channel Equalization: From Cyclostationarity to Subspaces", Signal Processing, pages 83-99, June, 1996). Unfortunately, none of the algorithms to date can handle multiuser CDMA communications.
In view of the basic principle that a CDMA system requires the signature waveform information at the base-station for reliable signal detection, and the fact that training sequence-based techniques are cumbersome in wireless communications, the lack of data efficient blind techniques has become a serious barrier to the implementation of a CDMA system in a frequency-selective environment. There is a critical need for new technology to effectively determine multiuser channel parameters and signature waveforms without the use of the training sequence. The current invention directly addresses this need. Here, we present a blind technique which provides closed-form estimates of the signature waveforms for an almost synchronized CDMA system. Our approach is deterministic in the sense that no noise or signal statistics are required for the estimation. The estimation is accomplished by exploiting the fact that the user's signature waveform is confined to a subspace defined by the its associated code. The principal advantage of this approach is that it is highly data efficient and most suitable for a rapidly changing environment. In particular, it can determine the signature waveform with the number of data samples as small as the number of co-channel users.